Tuesday, 31 May 2016

One of the peskiest problems of leaning too heavily on a gene-centric model
these days is that the definition of the word ‘gene’ gets ever more various and slippery.
Even as a technical term, the word carries at least a half-dozen meanings, and more are
added as science finds new tools for exploring the genome. This alone makes it either
a poor candidate for a popular meme — or, if you value flexibility over exactitude,
perhaps a perfect one, since its meaning can be defended or reshaped or expanded to
suit the occasion. If you expand the meaning to be ‘the thing essential to all true
heredity and selection’, you can then give the gene primary credit for any discovered
or proposed evolutionary force in which the gene seems to be involved — and reject
outright any proposed evolutionary force that doesn’t seem to involve genes.

"Gene" is indeed an overloaded term - but this type of overloading happens to many
popular terms. "Evolution, "selection" and "meme" have become similarly overloaded.
What happens is that when such terms become widely used, people adopt them, add their
own interpretations and bend them to their own ends. The term "gene" having multiple
meanings isn't a very good reason to reject it - rather it is a consequence of
its widespread popularity.

IMO, notions of "gene" that don't boil down to something like "unit of heredity" are
unscientific. The molecular biology definition of "gene" in particular is
very parochial and should not be used by anyone. Genetics is the science of heredity,
and genes are the units of heredity. I think there's room for debate about what
"heredity" means, but I don't see a coherent alternative to carving things up this way.

Genetics began as inferences about the nature and character of inheritance from observed patterns, not by understanding molecular biological mechanisms. Mendelian genetics flourished 50 years before the final understanding of its molecular basis in DNA.

Molecular biologists have appropriated the term "gene" to refer to stretches of DNA that code for a protein. Unfortunately, this sense differs from the one used in population genetics, behavioral genetics, and evolutionary theory, namely any information carrier that is transmissible across generations and has sustained effects on the phenotype. This includes any aspect of DNA that can affect gene expression, and is closer to what is meant by "innate" than genes in the molecular biologists' narrow sense.

Obviously, lots of other people disagree with me about the term "gene". Epigenetics and "not by genes alone" are examples of confusion over this issue. David Dobbs at least seems to recognize that his critique depends on using a narrow definition of "gene" - though he seems to think that using a broad definition leads to issues with falsifiability - which I would dispute.

The proponents of the "extended evolutionary synthesis seem to want to play down the revolutionary aspects of their proposals, but their proposed revolution has a number of things in common with the ideas I promote - so it seems appropriate to compare them.

At first glance their proposals are oriented around incorporating developmental biology into evolutionary theory. I recognize that developmental biology was left out of the modern evolutionary synthesis, but I wouldn't say that the focus of Universal Darwinism was putting it back in. This difference in perspectives gives our proposals a rather different slant.

The EES recognizes that inheritance results not just from genes but also through the transmission of a wide variety of resources (epigenetic marks, antibodies, hormones, symbionts, behavior, environmental states), through which parents construct developmental environments for their offspring. In the EES, heredity and development are closely intertwined and can include all causal mechanisms by which offspring come to resemble their parents."

IMO, this is the part of their proposal that most closely resembles Universal Darwinism. Universal Darwinism points out that copying operations are ubiquitous in nature, and are not confined to biology. High fidelity copying is also common. My main comment on their presentation is that it clearly does not go far enough. In particular, I see no sign of Darwinian physics in their presentation.

To their credit the proponents do extend inheritance beyond DNA and culture. They criticize 'dual inheritance' models of cultural evolution as ignoring other kinds of environmental inheritance and propose their own 'triple inheritance' models which don't have this defect. This material is all good and correct.

In Universal Darwinism, it isn't just inheritance that is "extended". It's all the operations found in more conventional evolutionary theory: copying, mutation, selection, filtering, sorting and merging. Do the proponents of the extended evolutionary synthesis recognize this? To some extent they do. Their presentation of this idea seems a bit odd to me, though. What they emphasize is what they call "multiple routes to the adaptive fit between organisms and environments". The basic idea here is that rather than just organisms adapting to environments, organisms change environments to suit themselves. Since they have organisms selecting environments as well as environments selecting organisms, this seems like a bit of an expansion of selection - compared with the conventional role of selection in evolutionary theory. However, this idea too seems watered down compared to the presentation typically found in Universal Darwinism.

I've previously commented about their terminology. They use the term "niche construction" use a lot, but have a confusing and counter-intuitive definition of it. According to them "niche construction" involves any change made by an organism to its environment. That mixes together niche creation and niche destruction. In my opinion, referring to destructive operations as "construction" gets confusing fast. I call their concept "environmental modification by organisms". I don't think it is important enough to deserve a snappier title. Things like "environmental modification", "niche creation" and "niche destruction" seem like better terminology to me.

They frequently use the term ecological inheritance. By contrast I more frequently use the term "environmental inheritance". I don't pretend these terms are synonyms, but they do represent competing terminology. Ecological inheritance seems like an umbrella term that includes organic inheritance. Environmental inheritance excludes organic inheritance. So we have Ecological inheritance = Organic inheritance + Environmental inheritance. It's nice to have an umbrella term, but IMO, usually what you want is something that contrasts with organic inheritance - not something that includes it.

I'm also concerned that their more revolutionary content is mixed up with a lot of more conventional material that will be regarded as being old hat.

Maybe there are some good things in their proposal that I'm currently missing, but my impression is that this is a watered down and inferior evolution revolution - when compared to the Universal Darwinism that I have been promoting. In fact, my reaction to their proposals has been similar to when I first read about Boyd and Richerson's version of cultural evolution. I felt as though the revolutionary content in memetics had been watered-down and stripped out, leaving a rather dry and boring husk. Perhaps watered-down content is all that academia is likely to stomach - but I want evolutionary theory to skip ahead a bit. The evolution revolution has already been going on for 150 years. How much longer is it going to take?

Sunday, 29 May 2016

Evolutionary biology is intimately involved with the topic of how information about environments is transmitted down the generations. There's a fairly mature mathematical framework which engineers use for discussing this sort of thing, namely Shannon/Weaver information theory.

Crick famously mentioned information when specifying the central dogma. However, over the years, a number of people have complained about attempts to apply information theory to biology. The complaints are various: information is subjective; it isn't clear how to apply the theory; information theory is confusing; organisms inherit more than just information from their ancestors; the results are not very useful - and so on. Others think an information-based analysis is useful, but prefer other information metrics.

I'm not talking about bits when I'm talking about information, I'm talking about information in a more fundamental sense. Shannon information measured in bits is a recent and very important refinement of one concert with information but it's not the concept I'm talking about. I'm talking about the concept with information where when one chimpanzee learns how to crack nuts by watching his mother crack nuts there's information passed from mother to offspring and that is not in bits, that is that is an informational transfer but has not accomplished in any Shannon channel that is worth talking about.

Attempts have been made to apply the Shannon-Weaver theory of communication to genetics but have typically failed to assist research (Hariri, Weber, and Olmsted 1990). The broader discipline of bioinformatics makes use of this and other analytic techniques to find patterns in data sets that may turn out to be functional or significant (Mount 2004), but such techniques require validation by experiment, and there is debate over how useful it is. Part of the problem with the Shannon account is that it is hard to find analogues for the general abstract entities of Shannon’s account.

Another common complaint is that creationists frequently use information theory to criticize evolutionary theory. Here, information theory seems to be getting tarred by association. For more examples, see the references of this post. I think that Shannon/Weaver information theory is applicable to evolutionary biology and is useful when applied there. This post is not really about that, though - instead it introduces a concept which I think is useful when applying information theory.

A conventional interpretation of the term "information" involves the "unexpected" content of a message. A novel message contains information; a message that you already know the contents of does not. This concept can be formalized and quantified if the observer places a probability density function over the domain of the expected input symbols before they receive them - allowing the 'surprise value' of the message to be quantified in bits.

However, this concept of information faces a problem when applied to scientific domains: namely, it is subjective. Two observers can easily differ on the issue of what the information content of a message actually is. Subjectivity is a problem in scientific domains: scientists go to considerable lengths to find objective metrics, to help other scientists reproduce their work. This post describes a way to resolve this issue.

It is true that the conventional interpretation of "information" is subjective. However, it is pretty easy to convert this into an objective metric - simply by specifying the observer involved. If scientists do not observe a message directly, but instead use a clearly-specified reference observer to observer it, they can agree on the information content of a message.

Reference observers are sometimes called "virtual observers" or "standard observers". To give an example of a reference observer, consider an agent with a maximum entropy prior over the available symbols and no memory or state variables. Such an observer would measure the information carrying capacity of a message. To such an agent, a 650 MB CD ROM would contain 650 MB of information. A 4.7 GB DVD would contain 4.7 GB of information - and so on.

Other portable observers could be based on standard compressors. PKZIP and GZIP are examples of widely available compression programs that could be used. They have their own prior probabilities and learning algorithms, and are standard and so can be specified by simply naming them.

A related complaint is that with lots of possible reference observers available, researchers will pick ones that promote their own theories or results, again eliminating the objectivity of science. That is a genuine concern. However pretty much the same problem applies to Kolmogorov complexity, or to priors in Bayesian statistics. This is a well-known issue which scientists should be familiar with handling. IMO, having multiple reference observers available is better than attempting to promote a one-size-fits-all scheme for measuring information scientifically.

I think that the concept of "reference observer" fairly neatly overcomes many of the objections to the use of Shannon/Weaver information theory which claim that information theory is subjective. If you specify the observer involved, the subjectivity vanishes. It can be complex to specify some observers - but other observers are very simple and easy to specify, and some standard observers are widely available.

Monday, 16 May 2016

Here are some of my books on memes and the evolution of culture. This is for anyone curious about my dead tree collection after reading some of my reviews. Moving to America in 2011 took my personal library through the eye of the needle - and not much made it through. These books are some of what I've been reading since then. These books are currently all within easy reach of my one-year-old daughter - so I thought I would snap them before they are reduced to shreds. Feel free to click if you would like to see bigger images.

Following Cavalli-Sforza, we call these units “semes” rather than “memes” (Dawkins 1976, Durham 1991, Boyd and Richerson 1985) because “seme” comes from “sign” and emphasizes the symbolic nature of culture.

Semes were apparently first mentioned in a 1970 book by Roland Barthes called "S/Z" - a three hundred page dissection of a short story written in French.

However, they were subsequently adopted by Cavalli-Sforza, Marc Feldman and others. Feldman explains the term in a 2007 presentation here. He presents "semes" as the cultural equivalent of "genes".

I call them semes because I don't like memes, memes gives some impression of biology which I do not want to do and semes comes from semiotics.

Of course, culture is part of biology, so biologically-inspired terminology is completely appropriate.

I think "semes" are more-or-less dead terminology now. Not all culture is symbolic, so the death of "semes" seems to be no great loss. However, IMO, it is fascinating historical tit-bit that Cavalli-Sforza and Marc Feldman join all the other students of cultural evolution that publicly toyed around with "-eme" words.

Friday, 6 May 2016

The concept of natural selection part of the core of Darwinian evolutionary theory. However
in my opinion, it has become muddied by definitional issues. One issue is the term has come
to cover a mixture of processes. It covers both death and reproduction. Another is that some
biologists decided they wanted to use the definition of natural selection to distinguish
between changes likely to produce adaptation and those likely to destroy adaptations -
creating a distinction between selection and drift. I'm not too happy about the results of that effort.

I've previously argued for a conceptual breakdown of natural selection into components representing
death and reproduction: natural
production and natural elimination. The rest of this post describes some orthogonal concepts.

The term "selection" commonly refers to a choice between alternatives - and the term
"natural selection" was coined to indicate that the chooser didn't have to be a breeder, or even an agent: nature
could choose. However, IMO, things went rather downhill for natural selection after that.
After a while, biologists started to use the term "subset selection" to refer to this simple
choosing but they decided that this wasn't much use when considering how a sexual population
produced the next generation, since that process also involved transformational changes. The
conception of selection was enlarged to handle this more complicated case. That was, I think
a big mistake.

Scientists outside biology have another word for "subset selection". They call it "filtering".
Filtering is an important process which explains a lot about adaptation in nature.
Filtering applies to organisms when they die. Filters may also be applied while choosing mates,
or during sperm competition. However, though filtering is an important concept, it doesn't
explain everything.

In computer science, filtering is often combined with sorting. Sorting is a common
and important process in nature. Rocks are sorted on beaches and molecules are
sorted in the atmosphere. I think we can get some clarity back by using the
terms "natural filtering" and "natural sorting" instead of "natural selection".
I have previously written
a whole article about natural sorting.

Unfortunately, sometimes explanations of natural phenomena in terms of filtering and sorting
can also become contrived. One problem is that filtering is a binary process: either items make
it through the filter or they don't. Filtering is a reasonable metaphor for life or death situations.
However it seems less applicable to other aspects of reproductive success. Offspring counts are still
somewhat discrete, and it could be argued that they consist of a series of selection events.
Resource acquisition can be treated in the same way: either an item of resources is obtained
or it isn't. However, here it looks as though we are approximating a continuous
function with a series of discrete steps. That kind-of works - but sometimes, it is just
contrived and pointless: shoehorning the phenomena into the model.

When phenomena appear continuous, using a continuous model makes sense. My proposal for a
continuous modeling framework involves the common concepts of "reward" and "punishment".
The idea is that events can have positive or negative on fitness. Positive impacts are rewards
and negative impacts are punishments. Other consequences of events are deliberately neglected -
for the sake of keeping things simple. As with natural selection, we can have agent-free
versions: natural reward and natural punishment.

Reward and punishment are common consequences of actions by agents. However here it is
important to remember that natural rewards and natural punishments may happen without
regard to the agents previous actions. There need not be any attempt reinforcing of
behaviour going on. Nature may be capricious.

In standard evolutionary theory, natural reward and natural punishment are currently
most frequently referred to as favorable and unfavorable selection pressures. What
I'm proposing here are new names for these existing concepts.

Reward and punishment are concepts from psychology. This is one of the expected
application domains. Rewards lead to reinforcement and reproductive success of
patterns af various levels in the brain, from synapses to axon firing patterns.
Similarly punishment results in weakening and destruction of such patterns. In
other words, use of these terms isn't intended as a metaphor, reward and punishment
in psychology would be a straightforwards applications of these evolutionary concepts.